Model comparison
GLM-4.5V vs Llama 3.1 Nemotron 70b Instruct
GLM-4.5V is the stronger model overall, scoring 39.8 to 37.6 on the Noometry Index.
Last verified . 12 shared benchmarks.
NVIDIASummary
- They share 12 benchmarks with published results for both. GLM-4.5V scores higher in 8 categories and Llama 3.1 Nemotron 70b Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.5V leads 52.5 to 48.4.
Side by side
| GLM-4.5V | Llama 3.1 Nemotron 70b Instruct | |
|---|---|---|
| Provider | Z.ai (Zhipu) | NVIDIA |
| Noometry Index | 39.8 | 37.6 |
| Released | 2025-08-11 | 2024-12-18 |
| Weights | Open | Open |
| Context window | 64K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $1.80 | — |
| Results tracked | 15 | 14 |
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Category by category
Coding GLM-4.5V leads
GLM-4.5V: 39.5 (#155), Llama 3.1 Nemotron 70b Instruct: 35.9 (#216)
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Coding | 1347 | 1272 |
| BigCodeBench Instruct | — | 38.7% |
| BigCodeBench Complete | — | 48.2% |
Reasoning GLM-4.5V leads
GLM-4.5V: 27.4 (#119), Llama 3.1 Nemotron 70b Instruct: 25.0 (#152)
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1334 | 1266 |
| Kagi LLM Benchmark | 59.8% | — |
Math GLM-4.5V leads
GLM-4.5V: 37.4 (#159), Llama 3.1 Nemotron 70b Instruct: 35.5 (#182)
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Math | 1354 | 1271 |
Knowledge GLM-4.5V leads
GLM-4.5V: 37.5 (#156), Llama 3.1 Nemotron 70b Instruct: 34.1 (#199)
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Expert | 1353 | 1242 |
Multimodal Not comparable
GLM-4.5V: 34.3 (#92), Llama 3.1 Nemotron 70b Instruct: —
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Vision | 1154 | — |
Multilingual GLM-4.5V leads
GLM-4.5V: 44.6 (#177), Llama 3.1 Nemotron 70b Instruct: 40.5 (#217)
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Non-English | 1303 | 1245 |
| LMArena Chinese | 1337 | 1263 |
| LMArena Russian | 1298 | 1227 |
| LMArena Spanish | 1336 | — |
Instruction Following GLM-4.5V leads
GLM-4.5V: 69.2 (#175), Llama 3.1 Nemotron 70b Instruct: 65.9 (#213)
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Instruction Following | 1311 | 1252 |
Long Context GLM-4.5V leads
GLM-4.5V: 39.6 (#171), Llama 3.1 Nemotron 70b Instruct: 37.6 (#215)
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Longer Query | 1304 | 1238 |
Writing & Preference GLM-4.5V leads
GLM-4.5V: 52.5 (#170), Llama 3.1 Nemotron 70b Instruct: 48.4 (#203)
| Benchmark | GLM-4.5V | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Text | 1333 | 1283 |
| LMArena Creative Writing | 1295 | 1269 |
| LMArena Multi-Turn | 1332 | 1275 |
Frequently asked questions
Is GLM-4.5V better than Llama 3.1 Nemotron 70b Instruct?
GLM-4.5V is the stronger model overall, scoring 39.8 to 37.6 on the Noometry Index.
Is GLM-4.5V or Llama 3.1 Nemotron 70b Instruct better for coding?
GLM-4.5V scores higher on coding benchmarks: 39.5 versus 35.9 in the Noometry coding category.
How many benchmarks do GLM-4.5V and Llama 3.1 Nemotron 70b Instruct share?
12 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Llama 3.1 Nemotron 70b Instruct has 14.